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Robust Bootstrap Densities for Dynamic Conditional Correlations : Implications for Portfolio Selection and Value-at-Risk

Trucíos, Carlos - 2017

the uncertainty is measured using bootstrap methods. We also propose a bootstrap procedure to obtain forecast densities …

Persistent link: https://www.econbiz.de/10012956168

Computationally efficient bootstrap prediction intervals for returns and volatilities in ARCH and GARCH processes

Chen, Bei; Gel, Yulia R.; Balakrishna, N.; Abraham, Bovas - In: Journal of forecasting 30 (2011) 1, pp. 51-71

Persistent link: https://www.econbiz.de/10009233916

Efficient Bootstrap Forecast Intervals for Return and Volatility Using the Linear Estimator of Arch Models

Iqbal, Farhat - 2020

using the bootstrap. Forecast intervals for returns and volatility are constructed using the linear estimator (LE) for ARCH …

Persistent link: https://www.econbiz.de/10012856558

Predictive quantile regressions under persistence and conditional heteroskedasticity

Fan, Rui; Lee, Ji Hyung - In: Journal of econometrics 213 (2019) 1, pp. 261-280

Persistent link: https://www.econbiz.de/10012304551

Small-sample properties of estimators in an ARCH(1) and GARCH(1,1) model with a generalized error distribution : a robustness study

Pauly, Ralf; Kosater, Peter - 2005

GARCH Models have become a workhouse in volatility forecasting of financial and monetary market time series. In this article, we assess the small sample properties in estimation and the performance in volatility forecasting of four competing distribution free methods, including quasi-maximum...

Persistent link: https://www.econbiz.de/10009660996